From 23461645ae66dad11d856fe60c69304e4407c61d Mon Sep 17 00:00:00 2001 From: royxroy Date: Wed, 4 Sep 2019 11:01:29 +0800 Subject: [PATCH] Add design.rst --- .../cluster.rst => design.rst} | 28 ++++++++---------- docs/images/parl.graffle | Bin 44845 -> 45292 bytes docs/index.rst | 2 +- docs/parallel_training/client.png | Bin 134671 -> 161832 bytes docs/parallel_training/cluster_structure.png | Bin 120580 -> 122255 bytes docs/parallel_training/master.png | Bin 201638 -> 200068 bytes docs/parallel_training/worker.png | Bin 241899 -> 240259 bytes parl/remote/client.py | 4 +-- 8 files changed, 16 insertions(+), 18 deletions(-) rename docs/{parallel_training/cluster.rst => design.rst} (89%) diff --git a/docs/parallel_training/cluster.rst b/docs/design.rst similarity index 89% rename from docs/parallel_training/cluster.rst rename to docs/design.rst index ce688ce..b2a76a8 100644 --- a/docs/parallel_training/cluster.rst +++ b/docs/design.rst @@ -1,11 +1,8 @@ Parl Cluster ============ -Get Started -########### - Cluster Structure Overview --------------------------- +########################## | There are three core concepts in a Parl cluster: master, worker and client. @@ -19,12 +16,13 @@ Cluster Structure Overview - **Client:** For each training program, there is a unique global client which submits tasks to the master node. -.. image:: ./cluster_structure.png +.. image:: ./parallel_training/cluster_structure.png :width: 600px :align: center Master ------- +###### + | There is only one master node in each parl cluster, we can start a master by calling ``xparl start --port 1234`` with a assigned port number. This command will also simultaneously start a local worker which connects to the new @@ -43,14 +41,14 @@ Master status of the cluster (i.e. total cpu number, used cpu number, load average ...) to the monitor. -.. image:: ./master.png +.. image:: ./parallel_training/master.png :width: 600px :align: center Worker ------- +###### -| We can add more computation resources to a existed cluster by calling +| We can add more computation resources to an existed cluster by calling ``xparl --connect master_address`` command. This command will create a local **Worker** object and then connect to the cluster. @@ -62,27 +60,27 @@ Worker job from the job buffer, start a new job and update worker information to the master node. -.. image:: ./worker.png +.. image:: ./parallel_training/worker.png :width: 600px :align: center Client ------- +###### | We have a global client for each training program, it submits training tasks to the master node. User do not need to interact with client object directly. - We can create a new global client or get an existed global client by calling + We can create a new global client and connect it to the cluster by calling ``parl.connect(master_address)``. | The global client will read local python scripts and configuration files, which will later be sent to remote jobs. -.. image:: ./client.png +.. image:: ./parallel_training/client.png :width: 600px :align: center Actor ------ +##### | **Actor** is an object defined by users which aims to solve a specific task. We use ``@parl.remote_class`` decorator to convert an actor to a @@ -108,6 +106,6 @@ Actor | When the actor call a function, the real computation will be executed in the job process by job's local actor. -.. image:: ./actor.png +.. image:: ./parallel_training/actor.png :width: 600px :align: center diff --git a/docs/images/parl.graffle b/docs/images/parl.graffle index 021d34a2b2e3381e97379ec4fb81e6832ddf0037..b0b0d57b3465a8836be03b87ecd8b086a3e7d590 100644 GIT binary patch literal 45292 zcmb^2bC6_BxG?zUw5@5|nx3|8O;1nTwr$(CZM(bLwr$%+ee=E-dt-Ow{;{zY6;GVX zljq6GIvEw2S-&ETfCl;J0S+)HDm7KYibM94tmAKm;Qh zs$`K>1S6RX$_#U|2>c8V?D=j`!c5CNeu&Ph+8-^5!u^C-2Ydux#J^adGpZ;gf4%e1 zKppU3eJo6NQXzbO626538PE8?a)9^m-Cz6{zSwHQSJo)v6_1<0N<2s$o(X}AroMwD zPq+xq16v3l`E2b0PAoW?AA~MIl$#b>jdVPeb;sG*cTk8 z>&?=ZPmghQ6aP7)=b7l$8}Q?6z5D3v3y3}`THO_V9Ywm*jWg)*vZl>&xwqHiQ?(?$ z0tA9*c#Ooez$UL6-~RAb>6^=zGw6P-5reb`jcOi+LJ#rkWr8KIg^TrJl~YR5(yiyv z=wnP3tLtu`bzj`vj-JWxYL*umly=q71_gP;Y0=<-8MM6_Vv-z)DvCy(O*S(Gl|=!8 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Attributes: - submit_task_socket (zmq.Context.socket): A socket which submits job to - the master node. + submit_task_socket (zmq.Context.socket): A socket which submits tasks to + the master node. pyfiles (bytes): A serialized dictionary containing the code of python files in local working directory. executable_path (str): File path of the executable python script. -- GitLab

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